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The study developed a two-level Bayesian framework to account for site specific variability in bias estimates for pile capacity evaluations using cone penetration test (CPT) data. The framework updated a weak prior for the bias factor with regional data in level 1 and with site specific data in level 2. A confidence bias site parameter was introduced to give more weight to site specific data. The framework improved existing methods by combining regional data, site specific data, and engineering judgement. The proposed approach was applied to assess the bias factors for pile capacity at three sites in Louisiana: Houma Bridge, Gibson Highway and Causeway Boulevard. The resulting bias factors were used to estimate the site-specific resistance factors for LRFD based design, which are typically calibrated using statewide or nationwide data. The results highlight that the selection of prior data in level 1 Bayesian analysis has little effect on the updated posterior data of specific site. In general, the updated posterior parameters for the specific new site lie between the prior2 parameters and the likelihood2 parameters, taking into consideration the specific site variability. Posterior2 data can be used to determine the LRFD resistance factor ( ϕ R ) for the design of piles based on pile-CPT design methods for the specific site. More weight should be given to new pile load test data using the confidence bias site parameter, which depends on the site condition and extent of testing. [ABSTRACT FROM AUTHOR]

Pile setup is defined as the increase in pile capacity with time. This increase in pile capacity starts immediately after end of driving (EOD). Majority of the setup conducted during the consolidation period followed by a small amount during the post-consolidation period. However, there is no available methodology to estimate the duration of setup during the consolidation period, and to establish a theoretical upper time limit for pile setup capacity beyond which pile setup capacity can be neglected. This paper examines or focuses to develop a methodology to estimate the time duration of pile setup. Three instrumented test piles (TPs) were driven mainly in clayey soil in Louisiana besides regular bridge construction projects. The piles were instrumented with sister bar strain gages to measure the load transfer along the piles' length, and four sets of pressure cells and piezometers were installed on each pile face to measure the total stress, effective stress and excess pore water pressure (PWP) with time. Dynamic and Static load tests were performed for a duration of 6 months after EOD and hence study setup. Piezocone dissipation tests were performed at each TP locations at different depths to measure the horizontal coefficient of consolidation (ch) besides the regular laboratory and in situ cone penetration test (CPT) to characterize the subsurface soil condition. The piezometers that were installed on the pile face showed that the dissipation continued from 2.5 h to 90 days after EOD depending on the soil properties. The equation that was proposed by Teh and Houlsby (Geotechnique 41(1):17–34, 1991) for dissipation test of piezocone was adopted to calibrate the time factor for pile. A new modified time factor for pile (Tpile*) was proposed in this study to estimate the duration of pile setup. [ABSTRACT FROM AUTHOR]

This paper presents the analyses of twelve prestressed concrete (PSC) instrumented test piles that were driven in different bridge construction projects of Louisiana in order to develop analytical models to estimate the increase in pile capacity with time or pile setup. The twelve test piles were driven mainly in cohesive soils. Detailed soil characterizations including laboratory and in situ tests were conducted to determine the different soil properties. The test piles were instrumented with vibrating wire strain gauges, piezometers, pressure cells that were monitored during the whole testing period. Several static load tests (SLTs) and dynamic load tests were conducted on each test pile at different times after end of driving (EOD) to quantify the magnitude and rate of setup. Measurements of load tests confirmed that pile capacity increases almost linearly with the logarithm of time elapsed after EOD. Case pile wave analysis program was performed on the restrikes data and was used along with the load distribution plots from the SLTs to evaluate the increase in skin friction capacity of individual soil layers along the length of the piles. The logarithmic linear setup parameter "A" for unit skin friction was calculated of the 70 individual clayey soil layers and was correlated with different soil properties such as undrained shear strength (Su), plasticity index, vertical coefficient of consolidation (cv), over consolidation ratio and sensitivity (St). Nonlinear multivariable regression analyses were performed, and three different empirical models are proposed to predict the pile setup parameter "A" as a function of soil properties. For verification, the subsurface soil conditions and setup information for additional 18 PSC piles collected from local database were used to compare the measured versus predicted "A" parameters from the proposed models, which showed good agreement. [ABSTRACT FROM AUTHOR]

This paper presents reliability-based analyses for the calibration of resistance factor for axially loaded drilled shafts. A total of 16 cases of drilled-shaft load tests were collected from the Louisiana Department of Transportation and Development (LADOTD) archives. Only 11 out of the 16 cases met the Federal Highway Administration (FHwA) failure criterion. Because of the limited number of available drilled-shaft cases in Louisiana, additional 15 drilled-shaft cases were collected from a neighboring state, Mississippi, which has subsurface soil conditions similar to Louisiana soils. A database of 26 drilled shafts representing the typical design practice in Louisiana was created for a statistical reliability analysis. Predictions of load-settlement behavior of drilled shafts from soil borings were determined using the FHwA design method through the SHAFT computer program. Measured drilled-shaft axial nominal resistance was determined from either the Osterberg cell (O-cell) test or the conventional top-down static load test. Statistical analyses were performed to compare the predicted ultimate drilled-shaft nominal axial resistance and the measured nominal resistance. Results show that the selected design method underestimates the measured drilled-shaft resistance by an average of 17%. The Monte Carlo-simulation method was selected to perform the LRFD calibration under strength I limit state. Total resistance factors for different reliability indexes (β) were determined and compared with those available in literature. The LRFD calibration showed that the FHwA design method has a resistance factor ([lowercase_phi_synonym]) of 0.60 at a target reliability index (βT) of 3.0. [ABSTRACT FROM AUTHOR]

Field and laboratory testing programs were conducted to develop resilient modulus prediction models for application in the design and evaluation procedures of pavement structures. The field testing program included conducting several in-situ tests such as Geogauge, Light Falling Weight Deflectometer, and Dynamic Cone Penetrometer (DCP). The laboratory program consisted of performing repeated load triaxial resilient modulus tests, physical properties, and compaction tests on soil samples obtained from tested sections. A total of four subgrade soil types at different moisture-dry unit weight levels were considered. Comprehensive statistical analyses were conducted on the field and laboratory test results. Two sets of models were developed. The first set (direct model) directly relates the laboratory measured resilient modulus values with the results of each of the three in-situ devices, whereas the second set (soil property model) incorporates soil properties in addition to the results of each of the three in-situ devices. A good agreement was observed between the predicted and measured values of the resilient modulus. Furthermore, the results showed that the resilient modulus prediction was enhanced when the soil properties were included as variables within the models. Among the models developed, the DCP-soil property model had the best prediction of resilient modulus followed by the DCP-direct model. The effectiveness of the DCP models were further evaluated during a forensic analysis of pavement section failure in a highway within Louisiana. [ABSTRACT FROM AUTHOR]

Current pavement design procedures recommend the resilient modulus of subgrade materials for pavement design and analysis. The objective of this paper is to develop two statistical models to predict the resilient modulus of subgrade cohesive soils from the dynamic cone penetration (DCP) test parameters and soil properties. The first model correlates resilient modulus to the dynamic cone penetration test parameters, while the second model correlates resilient modulus to both the dynamic cone penetration test parameters and soil properties. Field and laboratory experiments were conducted at 31 sites in Louisiana that contain four common soil types (A-4, A-6, A-7-5, and A-7-6). Field tests included DCP tests and soil sampling, while laboratory tests included determining basic soil properties and resilient modulus. Statistical analyses were conducted on the collected data, and two statistical models were developed for the prediction of resilient modulus of cohesive subgrade soils from the DCP test parameters and soil properties. The models predicted a separate data set that was not used in their development, indicating the success of the application of the dynamic cone penetration test in evaluating the resilient modulus of pavement subgrade soils. The predicted values obtained from the proposed models corresponded well with the measured resilient modulus values from the repeated load triaxial test. [ABSTRACT FROM AUTHOR]